Role Overview

Albany Beck are seeking an experienced Senior AI Engineer to lead the design, development, and deployment of advanced AI systems. This role focuses on leveraging large-scale data, building robust machine learning algorithms, and continuously evaluating and improving AI processes to drive measurable business impact.

You will play a key role in shaping AI strategy, managing infrastructure, and collaborating cross-functionally to define and achieve AI objectives.

Key Responsibilities

Data & Analysis

• Collect, process, and analyse large volumes of structured and unstructured data
• Design data pipelines to support scalable AI development
• Ensure data quality, governance, and integrity

AI Development & Engineering

• Program AI software to effectively leverage large datasets
• Develop, test, and deploy machine learning algorithms into production
• Optimize model performance, scalability, and efficiency
• Implement continuous improvement processes for AI systems

Evaluation & Optimization

• Evaluate machine learning workflows and model performance
• Design metrics and benchmarking frameworks to assess AI effectiveness
• Conduct experiments and performance tuning to improve outcomes
• Identify and mitigate bias, risk, and performance bottlenecks

Infrastructure & Project Management

• Manage AI-related data infrastructure and cloud environments
• Oversee project timelines and AI system lifecycle management
• Ensure systems are reliable, secure, and production-ready
• Support CI/CD processes for AI deployment

Collaboration & Leadership

• Collaborate with engineering, product, and business stakeholders to define AI goals
• Translate business requirements into technical AI solutions
• Provide guidance and mentorship to junior engineers
• Stay up to date on emerging AI research, tools, and industry best practices

Required Qualifications

• 5+ years of experience in AI, machine learning, or data engineering
• Strong experience collecting and analysing large datasets
• Proven track record of developing and deploying AI algorithms in production
• Proficiency in Python and common ML libraries (e.g., PyTorch, TensorFlow, Scikit-learn)
• Experience managing AI infrastructure and cloud environments
• Strong understanding of model evaluation techniques and performance metrics
• Experience collaborating across technical and non-technical teams